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Abstract:

Implementations of methods, apparatuses, or systems are disclosed to
facilitate search related communications.

Claims:

1. A method comprising: processing search queries based at least in part
on one or more search query parameters to identify candidate search
queries for an exchange of search related communications; wherein said
candidate search queries originate from different special purpose
computing system sources or different users.

3. The method of claim 1, and further comprising: initiating one or more
communication links for an exchange of search related communications
between respective sources of identified candidate search queries.

4. The method of claim 1, and further comprising: providing suggested
follow up queries based at least in part on said exchange of search
related communications.

5. The method of claim 3, wherein said initiating one or more
communication links for an exchange of search related communications
between respective sources of identified candidate search queries
comprises initiating one or more communication links for an exchange of
search related communications between respective sources of identified
candidate search queries via a discussion group.

6. The method of claim 3, wherein at least one of said one or more
communication links comprises a hyperlink.

7. The method of claim 1, wherein said one or more parameters or factors
comprise at least one of the following: time proximity; subject matter
relatedness; discussion-orientation; text-relatedness; click-relatedness;
result-relatedness; reformulation relatedness; or any combination
thereof.

8. An apparatus comprising: a special purpose computing system; said
special purpose computing system to process search queries based at least
in part on one or more search query parameters to identify candidate
search queries for an exchange of search related communications; wherein
said candidate search queries originate from different sources.

9. The apparatus of claim 8, said special purpose computing system
further to provide suggested follow up queries based at least in part on
said exchange of search related communications.

11. The apparatus of claim 8, wherein said one or more parameters or
factors comprise at least one of the following: time proximity; subject
matter relatedness; discussion-orientation; text-relatedness;
click-relatedness; result-relatedness; reformulation relatedness; or any
combination thereof.

12. An article comprising: a storage medium; said storage medium having
stored thereon instructions executable by a special purpose computing
system to process search queries based at least in part on one or more
search query parameters to identify candidate search queries for an
exchange of search related communications; wherein said candidate search
queries originate from different sources or different users.

13. The article of claim 12, said instructions to further provide
suggested follow up queries based at least in part on said exchange of
search related communications.

15. The article of claim 12, wherein said one or more parameters or
factors comprise at least one of the following: time proximity; subject
matter relatedness; discussion-orientation; text-relatedness;
click-relatedness; result-relatedness; reformulation relatedness; or any
combination thereof.

16. An apparatus comprising: means for processing search queries based at
least in part on one or more search query parameters to identify
candidate search queries for an exchange of search related
communications; and means for originating said candidate search queries
from different sources.

17. The apparatus of claim 16, and further comprising: means for
providing suggested follow up queries based at least in part on said
exchange of search related communications.

18. The apparatus of claim 16, wherein said means for processing search
queries based at least in part on one or more search query parameters to
identify candidate search queries for an exchange of search related
communications comprises means for processing search queries based at
least in part on one or more search query parameters to identify
candidate search queries for a real-time exchange of search related
communications.

19. The apparatus of claim 16, wherein said one or more parameters or
factors comprise at least one of the following: time proximity; subject
matter relatedness; discussion-orientation; text-relatedness;
click-relatedness; result-relatedness; reformulation relatedness; or any
combination thereof.

20. A method comprising: submitting one or more search queries from a
special purpose computing device or system; receiving a communication
link to participate in search related communications; and exchanging
search related communications via said communication link.

21. The method of claim 20, wherein said communication link comprises a
hyperlink.

23. An apparatus comprising: a special purpose computing system; said
special purpose computing system being capable of submitting one or more
search queries from a special purpose computing device or system;
receiving a communication link to participate in search related
communications; and exchanging search related communications via said
communication link.

24. The apparatus of claim 23, wherein said communication link comprises
a hyperlink.

Description:

[0004] Information in the form of electronic signals or information
continues to be generated or otherwise identified, collected, stored,
shared or processed. Databases or other like repositories of stored
information in the form of signals are common place, as are related
communication networks or computing resources that may provide access to
information. As one example, the World Wide Web provided by the Internet
continues to grow with seemingly continual addition of information.

[0005] Computing resources may enable users to access a wide variety of
stored signal information in the form of media content, including,
without limitation, text documents, images, video, or audio, to name just
a few examples. To provide access to stored information, tools or
services, such as search engines, for example, have been provided which
allow for relatively large amounts of stored information to be searched
in a reasonable period of time. However, with available stored
information continuing to increase, there is a continuing need for
effective searching capabilities.

BRIEF DESCRIPTION OF DRAWINGS

[0006] Claimed subject matter is particularly pointed out and distinctly
claimed in the concluding portion of the specification. However, both as
to organization or method of operation, together with objects, features,
or advantages thereof, it may be better understood by reference to the
following detailed description if read with the accompanying drawings in
which:

[0007]FIG. 1 is a schematic block diagram of an example computing
environment according to one implementation.

[0008]FIG. 2 is a flow diagram illustrating an example process to
facilitate search related communications according to one implementation.

[0009]FIG. 3 is a diagram depicting an example graphical user interface
according to one implementation.

[0010]FIG. 4 is a diagram depicting another example graphical user
interface according to another implementation.

[0011]FIG. 5 is a flow diagram illustrating an example process to
facilitate search query related communication according to another
implementation.

[0012]FIG. 6 is a flow diagram illustrating an example process to
facilitate search query related communication according to yet another
implementation.

DETAILED DESCRIPTION

[0013] In the following detailed description, numerous specific details
are set forth to provide a thorough understanding of claimed subject
matter. However, it will be understood by those skilled in the art that
claimed subject matter may be practiced without these specific details.
In other instances, methods, apparatuses or systems that would be known
by one of ordinary skill have not been described in detail so as not to
obscure claimed subject matter.

[0014] Reference throughout this specification to "one embodiment" or "an
embodiment" may mean that a particular feature, structure, or
characteristic described in connection with a particular embodiment may
be included in at least one embodiment of claimed subject matter. Thus,
appearances of the phrase "in one embodiment" or "an embodiment" in
various places throughout this specification are not necessarily intended
to refer to the same embodiment or to any one particular embodiment
described. Furthermore, it is to be understood that particular features,
structures, or characteristics described may be combined in various ways
in one or more embodiments. In general, of course, these and other issues
may vary with the particular context of usage. Therefore, the particular
context of the description or the usage of these terms may provide
helpful guidance regarding inferences to be drawn for that context.

[0015] Likewise, the terms, "and" and "or" as used herein may include a
variety of meanings that also is expected to depend at least in part upon
the context in which such terms are used. Typically, "or" if used to
associate a list, such as A, B or C, is intended to mean A, B, and C,
here used in the inclusive sense, as well as A, B or C, here used in the
exclusive sense. In addition, the term "one or more" as used herein may
be used to describe any feature, structure, or characteristic in the
singular or may be used to describe some combination of features,
structures or characteristics. Though, it should be noted that this is
merely an illustrative example and claimed subject matter is not limited
to this example.

[0016] Some portions of the detailed description are presented in terms of
algorithms or symbolic representations of operations on binary digital
signals stored within a memory of a specific apparatus or special purpose
computing device or platform. In the context of this particular
disclosure, the term specific apparatus, special purpose computing
device, or the like includes a general purpose computer once it is
programmed to perform particular functions pursuant to instructions from
program software. Algorithmic descriptions or symbolic representations
are examples of techniques used by those of ordinary skill in the signal
processing or related arts to convey the substance of their work to
others skilled in the art. An algorithm is here, and generally,
considered to be a self-consistent sequence of operations or similar
signal processing leading to a desired result. In this context,
operations or processing involve physical manipulation of physical
quantities. Typically, although not necessarily, such quantities may take
the form of electrical or magnetic signals capable of being stored,
transferred, combined, compared or otherwise manipulated. It is further
recognized that all or part of the various devices or networks described
herein, or the processes, methods, or operations as further described
herein, may be implemented using or otherwise include hardware, firmware,
software, or any combination thereof, although to be clear, this is not
intended to refer to software per se, which may constitute an abstract
idea.

[0017] It has proven convenient at times, principally for reasons of
common usage, to refer to signals as bits, data, values, elements,
symbols, characters, terms, numbers, numerals or the like. It should be
understood, however, that all of these or similar terms are to be
associated with appropriate physical quantities and are merely convenient
labels. Unless specifically stated otherwise, as apparent from the
disclosed subject matter, it will be appreciated that throughout this
specification discussions utilizing terms such as "processing,"
"computing," "calculating," "determining", "performing", "identifying",
"obtaining" or the like refer to actions or processes of a specific
apparatus, such as a special purpose computer or a similar special
purpose electronic computing device. In the context of this
specification, therefore, a special purpose computer or a similar special
purpose electronic computing device is capable of manipulating or
transforming signals, typically represented as physical electronic or
magnetic quantities within memories, registers, or other information
storage devices, transmission devices, or display devices of the special
purpose computer or similar special purpose electronic computing device.

[0018] For some search queries, such as subjective search queries, there
may not be suitable follow-up search queries to suggest to a user using
an automated process. Furthermore, some users may abandon search engine
use after a relatively short period of use or after "clicking" a few
links in returned search results at least in part because the results do
not appear close to the information they are seeking.

[0019] Likewise, communications among users via discussion groups or
social media related communications, such as via the Internet, for
example, appears to be increasing in popularity. Social communication
paradigms supported by the Internet, such as, for example, on-line social
networks or web-based personalized virtual communities continue to
evolve. Continued advancements in information technology, communications,
mobile applications, etc. help to bring on-line social networking. Social
networking is gradually becoming more widespread.

[0020] Accordingly, implementations of methods, apparatuses, or systems
are disclosed to facilitate search related communications between two or
more users of a search engine. Search related communications may include
electronic discussions between two users or more users, such as a group
of users, of respective special purpose computing devices, for example,
regarding one or many search topics, for example. As one example, without
limitation, users may be communicating via respective network clients,
although, of course, claimed subject matter is not limited in scope to
network clients.

[0021] Benefits of facilitating a communication exchange among users who
may be searching for similar or related information are currently
unrecognized, but potentially significant. Likewise, it may be difficult
to offer similar benefits through search algorithm advancement. In
effect, benefits of human creativity, intelligence, problem solving
ability, experience or subject expertise may potentially be leveraged in
a search environment shared by multiple users or participants. However,
to facilitate a communication exchange among users who may be searching
for similar or related information nonetheless has technical hurdles or
problems to be addressed, such as, appropriate user matching, timeliness,
privacy concerns, and user participation reluctance, to name only a few.

[0022] In at least one example implementation, users may interact with
other users conducting similar or related searches to discuss potential
follow-up search queries, obtain search query suggestions, or obtain
search results. For example, in at least one embodiment or
implementation, without limitation, one or more suggested search queries
may be provided, for example, by a special purpose computing device or
system, based, at least in part, on keywords obtained by processing of
communications between two or more users. Suggested search queries may
aid in obtaining search results, for example. However, claimed subject
matter is not limited in scope to a particular example implementation

[0023] Electronic communications or electronic discussions may be
implemented through any one of a host of various forms including, for
example, via text, audio, video, or other suitable exchange of electronic
signals or electronic information. Likewise, electronic communications or
electronic discussions may be implemented through any one of a host of
various special purpose computing devices, including, for example, a
laptop, a smart phone, or a personal digital assistant, to name only a
few, as described in more detail. Also as described in more detail,
electronic communications may aid users to formulate search queries or
obtain search results.

[0024] In at least one implementation, a special purpose computing device
may be identified and matched for communication with one or more other
special purpose computing devices. For example, without limitation, one
or more aspects or parameters of respective search queries may comprise a
basis at least in part for identifying and matching respective users. For
example, one or more search queries received from a variety of users may
be processed to identify one or more search queries in which one or more
parameters or aspects overlap with or have at least some commonality with
one or more other users' search queries. For example, in at least one
embodiment, a special purpose computing device from which a search query
has been received may be matched with another special purpose computing
device to facilitate communication between users of respective special
purpose computing devices, although, of course, claimed subject matter is
not necessarily limited in this respect.

[0025]FIG. 1 is a schematic block diagram of an example computing
environment 100 according to one implementation. As illustrated by FIG.
1, example computing environment 100 may include special purpose
computing devices or systems, such as 110, 114, 116, 118 or 120. Special
purpose computing devices or systems, such as 110, 114, 116, 118 or 120,
may, for example, comprise a desktop computer, a laptop computer, a
handheld computer, a mobile computing device, or other suitable media
device(s) that include computing capabilities along with the device(s),
such as, for example, a camera device, a telecommunications device, a
media player device, a personal digital assistant, etc.

[0026] For example and without limitation, device or system 110 may
comprise a server system. Likewise, one or more devices or systems, such
as 114, 116, 118 or 120 may, for example, but without limitation,
comprise a network client. Likewise, in at least one embodiment, devices
or systems, such as 110, 114, 116, 118 or 120, may communicate via a
network 112. For example, and without limitation, network 112 may
comprise one or more local area networks, one or more wide area networks,
one or more cell phone networks, one or more wireline telephone networks,
one or more personal area networks, the Internet or any combination
thereof, just to name a few possible examples. Likewise, it is, of
course, understood, that an implementation or embodiment is not limited
in scope to a particular number of special purpose computing devices.
Example computing environment 100 may include one, two, three, tens,
hundreds, thousands, millions, or more special purpose computing devices,
for example

[0027] Accordingly, devices or systems 114, 116, 118, or 120 may also
include storage media, such as, for example, 122 or 132, and one or more
processors, such as, for example, 124 or 134. Likewise, storage media,
such as 122 or 132, for example, may include instructions stored thereon,
such as 126 or 136, for example, that may be executable, for example, by
one or more processors to perform one or more operations, processes, or
methods, including those, for example, described in more detail
hereinafter. As one example, instructions 126 or 136 may comprise a web
browser application or other suitable program, software, or firmware,
etc. to retrieve, load, or process signal information (e.g., electronic
documents or the like), such as may be communicated between special
purpose computing devices, for example. Devices or systems 114, 116, 118,
or 120 may further include a communication interface, such as 103 or 138,
for example, to facilitate wired or wireless communication via network
112, for example, by transmitting or receiving signal information.

[0028] Systems or devices 114, 116, 118, or 120 may include one or more
peripherals, such as, for example, one or more input devices or output
devices. Non-limiting examples of input devices include a keyboard, a
touch-screen, a touch-pad, a microphone, a camera, or a pointing device,
such as a controller or a mouse, etc. Non-limiting examples of output
devices include an audio speaker, a tactile feedback device, a display, a
touch-screen, etc. In at least one implementation, devices or systems
114, 116, 118, or 120 may also include a graphical user interface (GUI)
application or other suitable program, software, or firmware, etc., such
as 142. As one example, execution of a GUI 142 may result in display of
icons or other small pictographs, such as in the form of bit maps, for
example, which may be capable of being viewed via an output device,
although this is merely one illustrative example.

[0029] Again, implementation or example 100 is provided for purposes of
illustration and claimed subject matter is not limited in scope to
implementation or example 100. For example, server system 110 may
comprise one or more computing platforms such as, for example, one or
more network servers. As alluded to previously, server system 110 may
include storage media 122 and one or more processors, such as example
processor 124. Also alluded to previously, storage media 122 may include
instructions 126 stored thereon that may be executable, for example, by
one or more processors, such as, for example, processor 124, to perform
one or more operations, processes, or methods, including, for example,
operations, processes, or methods described in more detail hereinafter.
Storage media 122 may further include an electronic repository to store
signal information, such as database system 128, for example. Likewise,
one or more processors of system 110, such as, for example, processor
124, may be capable of writing signal information to or reading signal
information from storage media 122, for example. Likewise, as also
alluded to above, server system 110 may further include a communication
interface 130 to facilitate wired or wireless communication via network
112, such as transmitting or receiving electronic signal information, for
example.

[0030] For example, a special purpose computing device may process search
queries received from one or more of devices 114, 116, 118, or 120, for
example. In this context, a search engine, such as a web search engine,
for example, refers to software or code, such as implemented by a special
purpose computing device or system, to search accessible information that
may be stored on storage medium. Storage mediums searchable by a search
engine may be accessible via direct or indirect electrical connection or
coupling, such as via a wire line or wireless network, including, for
example, a local area network, a wide area network, or the world wide
web, to provide a few example. Search results, sometimes referred to as
hits, may generally be presented in a list of results that may appear in
a user's browser that is executing on a special purpose computing device
or system that the user employed to enter the search query. A search
query, such as a web search query, for example, refers to a query that a
user may enter into search engine to seek particular information that may
be included among accessible stored information stored. Search queries
although typically provided in a particular language tend to be
unstructured. A search engine may be implemented to process search
queries, such as, for example, in connection with a search index
corresponding to search results for a given search query. Likewise, in at
least one implementation, a search log of search results from search
queries may be employed. A log typically refers to a file of
communications, such as transactions, between a system, such as server
system 110, as a non-limiting example, and users in communication with
the system. Typically, logs, such as transaction logs, are electronically
recorded interactions between on-line information retrieval systems and
users who search for information that may be found on those systems.

[0031] For example, if a special purpose computing device were to submit a
search query, in at least one embodiment, a search log may be updated to
include or indicate, for example, one or more search terms of the search
query and the corresponding special purpose computing device. Although
claimed subject matter is not limited in scope in this respect, terms,
such as click log, search log, search query log and session log may be
employed in connection with various embodiments. Therefore, terminology
as follows is employed herein: click log refers to a log for tracking
hyperlinks a user has `clicked through`; search log refers to a log for
tracking searches conducted by a user, irrespective of having clicked
through particular hyperlinks; search query log is another term for
search log; and session log refers to a log for tracking a user's search
or clicks during a session. A session, for example, may comprise a series
of interactions, for example, in which a client device and a server
device, for example, may be in contact but without significantly long
interruptions or breaks in communications. In addition or alternatively,
a search session may be related to user engagement, such as user
interactions recorded within a window of X minutes, for example, or
interactions until a user "appears" or is perceived to have received a
satisfactory result.

[0032] In at least one implementation, processing or filtering of search
queries may take place. For example, in at least one implementation,
processing or filtering may be based, at least in part, on one or more
parameters or aspects of search queries submitted from corresponding
special purpose computing devices. For example, separate search queries
from submitted from corresponding special purpose computing devices may
be identified as being related.

[0033] Likewise, in at least one implementation, communication between
computing devices or systems may be facilitated by initiating a
communication link between computing devices or systems identified as
submitting related queries, for example, as a result of search query
processing. In at least one embodiment, computing devices or systems may
communication via bi-directional signals, for example. As indicated
previously, communication signals may comprise any one of a host of types
of content, including, for example, text messages or content (e.g.,
instant messages, email, etc.), audio messages or content (e.g., voice),
image content, video content, multi-media content, etc.

[0034] In at least one embodiment or implementation, for example, an
assistance layer of a search engine may allow users to socialize or group
together to engage in search related communications, as described in more
detail below. For example, in at least one embodiment or implementation,
again, described in more detail below, after posing a query, for example,
users may be provided an opportunity to join a discussion related to the
particular query.

[0035]FIG. 2 is a flow diagram illustrating an example process 200 to
facilitate search related communications according to one implementation.
At 208, one or more search queries may be received or may have been
submitted or initiated. For example, a special purpose computing device,
such as 114, 116, 118 or 120, for example, may submit queries. Likewise,
a server system, such as server system 110, for example, may receive
search queries, such as via network 112, for example.

[0036] At 210, search queries received (e.g., operation 208) may be
logged, such as at a database system, for example. In this particular
context, logging refers to tracking, such as by storing, an indication of
one or more terms (e.g., keywords) included in the search query along
with an indication of a special purpose computing device origination or
source of the query. At 212, one or more search queries logged may be
processed or filtered based, at least in part, on one or more parameters
to identify candidate search queries that may be related or overlap in
subject matter in one or more aspects. For example, as a result of
identifying a candidate search query in 212, at 214, search related
communications may be facilitated in an embodiment, for example, by
inviting a special purpose computing device or system corresponding to
the candidate query to join a discussion group related to subject matter
of the candidate query. However, if no discussion group related to
subject matter is on-going, for example, but, at 214, two or more search
queries are identified to be related or overlap in subject matter in one
or more aspects, communication between special purpose devices
corresponding to the identified may be facilitated. For example, one or
more communication links to facilitate communication between
corresponding communications devices may be initiated, as described in
more detail below. As shall be described, a server or server system may
be employed to initiate a discussion. Typically, search queries go to a
main server anyway. Therefore, it may be convenient to employ a main
server to likewise decide which users join which chat conversations. Of
course, after a connection and a chat has been initiated, the users could
potentially chat in a peer-to-peer fashion in at least one
implementation. However, in an implementation, a server may also suggest
other searches/entities. This feature may be implemented more easily by
being included in a chat conversation in real-time and suggesting other
searches/entities.

[0037] Although claimed subject matter is not limited in scope in this
respect, below at least one possible implementation is provided as an
illustrative example of an approach to identifying two or more candidate
search queries for which facilitating communication between corresponding
computing devices or systems may be desirable or useful. For example, one
or more search queries received from a variety of users may be processed
to identify one or more search queries in which one or more parameters or
aspects overlap with or have at least some commonality with one or more
other search queries. Of course, as discussed below in more detail for at
least one implementation, there may be any one of a number of potential
aspects or parameters to consider. A range of parameters or factors may
exist for processing or evaluation that may tend to indicate that
facilitating communication between corresponding computing devices or
systems may be desirable or useful. Claimed subject matter is not limited
in scope to parameters or aspects discussed below as an illustrative
example. Of course, over a period of time, as experience is gained in
search related communications, additional parameters or factors to
consider may come to light. It is intended that claimed subject matter
cover such additional parameters and factors. Without limitation, useful
parameters or factors may later be found to be: topics raised in follow
on communication exchanges for similar searches performed; links that a
user clicked more frequently in previous searches; identification of
"entities" (e.g., organizations, companies, etc.) mentioned in follow on
communication exchanges and showing corresponding entity pages; or
specific link recommendations proposed during follow on communication
exchanges, as examples.

[0038] In at least one implementation, without limitation, two or more
search queries may be processed in a number of ways or along a number of
parameters. For example, given two search queries, in at least one
embodiment, the two search queries may, in effect, be compared and the
comparison may be evaluated or measured along a host of parameters or
aspects. Likewise, signal sample values may, for example, be employed as
a measure or score along a particular parameter, for example, of a search
query or a comparison of search queries. Likewise, different signal
sample values along different particular parameters or aspects may be
factored differently in terms of scoring, for example. It is noted that
comparison does not necessarily need to be pair wise between queries.
Rather, although claimed subject matter is not limited in scope in this
respect, for at least one implement, a comparison is made between a
search query, and existing on-going search related communications. So if
a query is similar to queries for an existing on-going search related
communications, a user may be added to that conversation.

[0039] As explained in more detail below, for at least one particular
implementation, queries may be evaluated in terms of query classification
or query relatedness. In one example, query relatedness may refer to
queries meeting identified or selected thresholds for subject matter
relatedness and time proximity. Thus, for this example, parameters for
measuring or scoring two search queries as being related may comprise,
without limitation: subject matter relatedness and time proximity. In
this context, queries may exhibit subject matter relatedness if one or
more measurable or scorable parameters or aspects of the queries overlap
with or have at least some commonality. Likewise, query classification
may refer to categorizing or classifying queries having common
properties. As example, an information query may refer to a query that
may cover a broad topic. In contrast, a navigation query may refer to a
query seeking a single or small number of websites or web pages. Of
course, these are merely two illustrative examples of query
classifications and are not intended to limit the scope of claimed
subject matter. In at least one particular embodiment,
discussion-orientation may comprise a search query classification
parameter to be scored or measured. In this context, a search query may
be classified as discussion-oriented if, given the query, a user may
benefit from user interaction regarding the subject matter of the query.
Of course, again, a host of other potential parameters or aspects may be
measured or scored and claimed subject is not limited in scope to any
particular parameters or aspects.

[0040] For example, a value to measure or score subject matter relatedness
and a value or score to measure time proximity may be calculated, as
described in more detail below. These signal sample values may likewise
be respectively weighed and combined to obtain a total signal sample
value Vt for a search query in at least one implementation.
Respective weighting factors W1, W2, etc. having suitable
values to capture a trade off may be employed in at least one
implementation. For example, but without limitation, a supervised model
(e.g., linear regression model or Support Vector Machine, for example)
may be employed to select weights over a training set.

[0041] Processing of search results to identify candidate search queries
may comprise selecting one or more search results having more extreme
total values Vt in at least one implementation. However, in other
implementations, one or more parameters or factors, such as subject
matter relatedness or time proximity, for example, may be evaluated on
another basis. However, continuing with the example or approach suggested
above, for at least one implementation, to identify a subject matter
relatedness signal sample value or score V1 in a comparison of
search queries, a search log, for example, may be referenced, as
explained in more detail below. For example, a first search query may be
considered to have perfect or nearly perfect query relatedness to a
second search query if two queries being compared are identical. In this
context, two queries are considered identical if they are the same after
applying standard natural-language transformations, such as term stemming
(e.g., to identify root forms of terms). Typically, grammar-specific
lexical rules, dictionaries or resources, such as WordNet, may be
employed. For example, existing methods such as Porter Stemmer may be
applied.

[0042] In situations involving identical queries, a time proximity
threshold may be an appropriate parameter or factor to apply to identify
candidate queries. However, search queries having perfect query
relatedness may not necessarily be found in some examples.

[0043] Furthermore, a user may benefit from communications with other
users even if respective search queries are not `identical.` However, in
situations in which respective queries are not identical, a measure or
scoring of sufficient subject matter relatedness may be appropriate.

[0044] For example, in at least one implementation, subject matter
relatedness may be scored or measured in at least one embodiment by
computing a subject matter relatedness sample signal value or score
V1 between a first search query (Q1) and a second search query (Q2).
A subject matter relatedness value V1 between Q1 and Q2 may,
however, be based, at least in part, on one or more other factors or
parameters. Example factors, without limitation, may include a
text-relatedness factor or parameter measured as a signal sample value
R1, a click-relatedness factor or parameter measured as a signal
sample value R2, a result-relatedness factor or parameter measured
as a signal sample value R2, and a reformulation-relatedness factor
or parameter measured as a signal sample value R4. The terms
text-relatedness, click-relatedness, result-relatedness and
reformulation-relatedness refer to, respectively, queries being related
in terms of text; queries being related in terms of users clicking
through to common locations or URLs; queries being related in terms of
search results produced; or queries being related in that their
reformulations are related in terms of text, click or result. Approaches
for calculating these parameters or factors are discussed in more detail
below. Of course, claimed subject matter is not limited in scope to these
particular factors or to this particular combination. Any of a host of
factors for scoring may be employed in other implementations. Likewise,
as discussed previously, different signal sample values along different
particular parameters or aspects may be factored differently in terms of
scoring, for example, using respective weighting factors W5,
W6,W7,W8 etc., again, for example, to reflect potential
tradeoffs. Again, for example, but without limitation, a supervised model
(e.g., linear regression model or Support Vector Machine, for example)
may be employed to select weights over a training set. As one example, a
text-relatedness parameter or factor may be identified by applying
natural-language transformations such synonyms, term stemming (e.g., to
identify root forms of terms), etc. to one or more search terms of Q1 and
Q2. Examples, without limitation, of articles related to this subject
include: Julie Beth Lovins, "Development of a stemming algorithm,"
appearing in Mechanical Translation and Computational Linguistics (1968);
and Eija Airio, "Word normalization and decompounding in mono- and
bilingual IR" appearing in Information Retrieval (2006).

[0045] In at least one implementation, a first search query may be
considered to satisfy a threshold level of text relatedness to a second
search query even if some or no search terms are identical. For example,
search queries "things to do in the bay area" and "bay area day trips"
may be considered related queries having a relative high relatedness for
at least one implementation. Likewise, in at least one implementation, a
first search query may be considered to satisfy a threshold level of text
relatedness to a second search query if root forms of one or more search
terms are identical or synonymous. For example, a search term "running"
may be evaluated as comprising a root form "run" for purposes of
comparing search queries.

[0046] In at least one implementation, click-relatedness parameter or
factor may be identified from click-logs. Click logs (also referred to as
"click-through") may track for a query links that were clicked by a user
among those presented by a search engine. For example, by determining how
frequently (e.g., in the past) search queries Q1 and Q2 have resulted in
users navigating (e.g., clicking through) to identical network locations
(e.g., electronic documents) via respective search results returned
responsive to search queries Q1 and Q2. Frequency of which search queries
Q1 and Q2 have resulted in users navigating to identical network
locations (e.g., universal resource locators (URL(s)) may, for example,
typically be expressed as an increasing function of a click-relatedness
parameter or factor. For example, if users navigate to identical
documents responsive to search queries Q1 and Q2 more frequently,
typically a higher click-relatedness parameter or factor may result.

[0047] In at least one implementation, a result-relatedness parameter or
factor may be determined, for example, based at least in part on a tf-idf
(term frequency-inverse document frequency) similarity of a set of top-K
search results on posing Q1 and Q2 to a particular search engine, for
example, where K comprises a positive integer value. A frequency measure,
such as tf-idf, may comprise a statistical measure of relevance for a
given term to an electronic document in a collection. Relevance may
typically comprise, for example, an increasing function of a number of
times a term appears in a document in a collection, but may be offset by
a frequency of the term in the collection. In at least one embodiment, a
reformulation-relatedness parameter or factor may be identified by
determining reformulations of search queries Q1 and Q2 from past
search-logs, such as search engine logs that may track user interactions
(e.g., query, clicked URLs, etc.) and recursively considering one or more
of a text relatedness parameter, a click-relatedness parameter, a result
relatedness parameter, etc. for reformulations. Query reformulations, for
example, may comprise pairs of queries where search engine users may
refine or alter their original or initial queries to better represent
their search goals. Reformulations may be mined, for example, from search
user query logs by focusing on user sessions and considering refinements
of queries within a session as candidate query reformulations.
Statistical measures such as co-occurrence frequency or point-wise mutual
information (PMI) may likewise be applied to identify more reliable
reformulations.

[0048] In at least one implementation, processing search queries received
or submitted may be based, at least in part, on time proximity (e.g.,
represented by a signal sample value corresponding to a time proximity
parameter or factor). For example, respective times at which search
queries may be received or submitted may be a factor for evaluation or
scoring. For example, a time proximity threshold may be implemented so
that search queries that are more proximate in time than the time
proximity threshold are more likely to be considered as candidate queries
to be identified. Accordingly, a time proximity of two search queries may
be expressed as a decreasing function of a time proximity signal sample
value, in at least some examples, such that more time proximate search
queries have higher time proximity signal samples values than less time
proximate search queries.

[0049] Furthermore, in at least one implementation, a search query may be
classified as discussion oriented based at least in part on being
evaluated or scored in terms of discussion-orientation. As one example, a
search query may be identified as a discussion-oriented query if the
search query may be considered argumentative, debatable, or subjective
such that it may benefit from communication between two or more users.
For example, a search query such as "things to do in the bay area" or
"best vacation destination" may be identified as a discussion-oriented
query. However, a more objective search query such as proper name (e.g.,
"Yahoo" or "CNN") may not be identified as a discussion-oriented query in
at least some implementations, for example.

[0050] To score or measure discussion-orientation, in at least one
implementation, for example, a search query log may be referenced or
processed to construct a click vector for a given search query, for
example. A click vector may comprise one or more search results (e.g.,
one or more uniform resource locators (URL)s) that were returned for a
given search query that were also selected (e.g., clicked) by one or more
users. Queries do not need to be identical or related. For example, one
may mine and discover related queries that were not known previously, for
example, by applying similarity of click vectors. A weight associated
with a search result (e.g., URL) for a given search query may be assigned
to that search result based, at least in part, on a frequency at which
that search result was selected (e.g., clicked) by one or more users.

[0051] A search query may be identified as a query scored relatively low
for discussion-orientation if, for example, a click vector comprises a
single entry for a single search result. In practice, for example, one
may expect a query to be scored relatively low for discussion orientation
if a relatively small number of entries for a relatively small number of
search results were selected by one or more users for a given search
query.

[0052] In at least one implementation, a signal sample value or score
V4 for discussion orientation may comprise a click-entropy value
computed using a click vector. Click-entropy is computed much like in
communication or information theory. See, for example, Jaynes, E. T.,
"Information Theory and Statistical Mechanics" appearing in Physical
Review (May, 1957). A click-entropy value, for example, may comprise a
measure of a degree of randomness (e.g., a level of diffusivity) of a
click vector. A search query having a click-entropy that is greater than
a threshold value may be employed, for example.

[0053] In at least one implementation, search queries received or
submitted may likewise be evaluated for language commonality. For
example, search queries in distinctly different languages, such as
English, French, Japanese, etc., typically may not be viewed as related
unless translations to a common language were first applied.

[0054] Returning to FIG. 2, as mentioned previously, at 214, communication
may be facilitated (e.g., a communication link may be initiated). In at
least one implementation, facilitating communication by initiating a
communication link may comprise, as illustrated in FIG. 3 by reference
numerals 316 or 318, for example, providing a link on a search results
page "join public discussion" or "join private discussion." Of course,
this is merely an illustrative example and claimed subject matter is not
limited in scope in this respect. Any one of a number of techniques or
approaches to initiate a communication link is possible and claimed
subject matter is not limited in scope to any particular technique or
approach.

[0055] For example, without limitation, a communication link may be
initiated between network clients by a server system. In at least one
implementation, facilitating communication between computing devices or
systems, for example, may comprise facilitating a real-time or live
communication. A real-time or live communication may, of course, comprise
communication delays that may occur for any one of a number of technical
reasons. A first user may, for example, submit a communication via a
network client that may be transmitted to another network client of a
second user via a server system to encourage real-time communications
regarding search query formulations.

[0056] In at least one implementation, a length or duration of
communication between two or more network clients may be limited. For
example, a length of a communication may be limited to N characters,
terms, or discussion text entries, where N may comprise a positive
integer. As another example, in various ways, duration of communication
may be limited to a value of N seconds, minutes, or hours, or other
suitable limiting condition. For example, a complete exchange of
communications may be limited in time or the time between communication
responses may be limited, as examples.

[0057] Referring to FIG. 5, in an additional implementation or embodiment,
for example, at 216, communications exchanged in connection with search
related communications may be processed to identify one or more keywords.
For example, suggested search queries that may be provided, such as via a
server or server system, for example, in at least one implementation.
This is illustrated, for example, at FIG. 4 by reference numeral 410. Of
course, claimed subject matter is not limited in scope to providing
suggested search queries.

[0058] In at least one implementation, at 216, search related
communications may comprise processing on-going communications to
identify one or more keywords that may comprise one or more suggested
search terms of a suggested search query. In addition to keywords,
suggested queries may be formulated potentially by identifying
interesting text segments, such as entities or query-like segments in
follow-on search query communications, for example.

[0059] At 218, transmission may be initiated of one or more keywords, such
as one or more keywords identified at operation 216. In at least one
implementation, electronic communications comprising one or more keywords
may be transmitted by a server system to appear on a search page of a
user as one or more hyperlinks, such as illustrated in FIG. 4, for
example. As one example, keywords may be mirrored to users of a
discussion group.

[0060] Likewise, in an alternate embodiment, for example, ongoing search
related communications may be annotated by referencing a reference
library of entities. A library may be constructed using any suitable
resource, such as Wikipedia, Wordnet, or other remote resource, for
example. Likewise, in at least one implementation, surface-level features
of a search query may be employed, such as term capitalization (e.g.,
Academy of Sciences), which denotes proper entities while ignoring
prepositions or other term modifiers. Of course, again, claimed subject
matter is not limited in scope in this respect.

[0061]FIG. 6 is a flow diagram illustrating another example process 600
to facilitate search related communications according to one
implementation. Whereas FIGS. 2 and 5 provide perspectives from a server
system, for example, a client system perspective may be illustrated by
this implementation or embodiment. For example, at 608, a search query
may be submitted from a special purpose computing device or system.
Likewise, as illustrated at 610 and described in more detail below, a
communication link or other invitation may be received to participate in
search related communications, such as a discussion group, for example,

[0062]FIG. 3 is a diagram depicting an example graphical user interface
(GUI) 300 according to one implementation. GUI 300 may be presented, for
example, via a display, as previously described. GUI 300 may comprise a
search field 310 to receive one or more search terms for enabling a user
to submit or initiate a search query. Search queries received via a
search field, such as search field 310, may be transmitted to a server
system, such as server system 110, for processing. GUI 300 may comprise
one or more search results 312 that may be returned by a server system,
such as server system 110, responsive to a search query received via
search field 310. As mentioned previously, GUI 300 may comprise one or
more suggested search queries 314. Likewise, a user may initiate a
follow-up search query by selecting one or more of suggested search
queries 314.

[0063] As mentioned previously, GUI 300 may comprise one or more
hyperlinks 316 and 318 to enable a user to initiate discussion
communication link with one or more other users via a discussion group,
for example. For example, a server system receiving a communication
initiation request as a result of a user selecting a hyperlink may
facilitate communication by exchanging search related communications
among users via participating computing devices or systems, for example.
Of course, claimed subject matter is not limited in scope in this
respect. Any one of a number of techniques or approaches may be employed.

[0064] In at least one implementation, as illustrated, 316 may comprise a
hyperlink or other suitable selector to enable a user to join a public
discussion. In this particular example, first selector 316 recites: "Join
Public Discussion!" notifying a user that a public discussion may be
joined by the user selecting first selector 316. A second selector 318,
for example, may comprise a hyperlink to enable a user to join a private
discussion. In this particular example, second selector 318 recites:
"Join Private Discussion!" notifying a user that a private discussion may
be joined by the user selecting second selector 318. Of course, in at
least one implementation, communication may be facilitated without
employing hyperlinks such as 316 or 318. Therefore, selectors or
hyperlinks 316 or 318 may be omitted in alternative embodiments, for
example.

[0065] Nonetheless, a private discussion may enable a user to restrict
communication with one or more other users to a subset of users. For
example, a private discussion may enable a user to restrict participation
in a discussion group. In particular, users may initiate a "private"
discussion wherein specified users, such as those defined via messenger
identifiers, email addresses, or other suitable identifier, may be
identified for communication. Likewise, a user may be prompted, for
example, to provide a list for a private discussion group.

[0066]FIG. 4 is a diagram depicting another example GUI 400 according to
one implementation. In this particular example, GUI 400 may illustrate a
search results page for a user participating in a public discussion
group. However, a similar approach may be utilized for a private
discussion group, of course. As illustrated in FIG. 4, for at least one
implementation, a portion of a search results page 410 may comprise a
field 412 to receive a communication submitted by a user may appear on a
search results page. A communication may take any one of a number of
possible forms and claimed subject matter is not limited in scope to a
particular form. For example, a free-form natural language communication
may be submitted in at least one implementation. Likewise, 410 may
comprise a discussion history 414 of communications from other users
participating in a discussion group. In this example, a discussion
history may be presented with respective time stamps (e.g., T1, T2, T3,
etc.) indicating a time at which a communication was received, for
example. Of course, claimed subject matter is not limited in scope to
this particular implementation. Again, this example is provided primarily
for purposes of illustration.

[0067] GUI 400 further depicts how keywords contained in communications
may be presented as keyword hyperlinks, for example, as indicated at 416
and 418. Keyword hyperlinks may be selected by a user to initiate a
search query for the one or more keywords of the selected keyword
hyperlink. In at least one implementation, one or more of search results
312 of GUI 400 may further include a selector 422 (e.g., an icon) for
enabling a user to copy and paste a select search result into discussion
field 412, enabling a user to more easily communicate search results to
another user, for example. Again, of course, claimed subject matter is
not limited in scope in these respects.

[0068] As an example discussion provided via a communication link may
comprise the following: User 1: "Any recommendations?" User 2: "During my
last visit, I visited the Computer Science Museum. It was great!" User 2:
"Also, the Academy of Science should be open to public now." User 1:
"Thank you!" A server system, such as 110, may identify suggested search
queries. For example, search queries including "Computer Science Museum"
or "Academy of Science" may be suggested to the first user or the second
user as one or more suggested search queries.

[0069] Communication facilitated between two or more users in the context
of a search activity may increase the extent to which search assistance
is provided to users of a search engine. For many search queries, such as
subjective search queries, there may not be suitable follow-up search
queries to suggest to a user using an automated process. A crowd-sourcing
principle may be applied to allow users to discuss their search results
or search tasks. Accordingly, search processes may be augmented with
human interactions that may provide benefits, such as human experience,
creativity, etc. Communication facilitated between two or more users in
the context of information searches may reduce abandonment rate among
users of a search engine. Furthermore, discussions facilitated between
two or more users in the context of information searches may further
encourage users to spend more time interpreting and understanding search
results.

[0070] It will, of course, also be understood that, although particular
embodiments have just been described, claimed subject matter is not
limited in scope to a particular embodiment or implementation. For
example, one embodiment may be in hardware, such as implemented on a
device or combination of devices, as previously described, for example.
Likewise, although claimed subject matter is not limited in scope in this
respect, one embodiment may comprise one or more articles, such as a
storage medium or storage media, for example, that may have stored
thereon instructions executable by a specific or special purpose system
or apparatus. As one potential example, a specific or special purpose
computing platform may include one or more processing units or
processors, one or more input/output devices, such as a display, a
keyboard or a mouse, or one or more memories, such as static random
access memory, dynamic random access memory, flash memory, or a hard
drive, although, again, claimed subject matter is not limited in scope to
this example.

[0071] In some circumstances, operation of a memory device, such as a
change in state from a binary one to a binary zero or vice-versa, for
example, may comprise a transformation, such as a physical
transformation. With particular types of memory devices, such a physical
transformation may comprise a physical transformation of an article to a
different state or thing. For example, but without limitation, for some
types of memory devices, a change in state may involve an accumulation
and storage of charge or a release of stored charge. Likewise, in other
memory devices, a change of state may comprise a physical change or
transformation in magnetic orientation or a physical change or
transformation in molecular structure, such as from crystalline to
amorphous or vice-versa. The foregoing is not intended to be an
exhaustive list of all examples in which a change in state for a binary
one to a binary zero or vice-versa in a memory device may comprise a
transformation, such as a physical transformation. Rather, the foregoing
are intended as illustrative examples.

[0072] A storage medium typically may be non-transitory or comprise a
non-transitory device. In this context, a non-transitory storage medium
may include a device that is tangible, meaning that the device has a
concrete physical form, although the device may change its physical
state. Thus, for example, non-transitory refers to a device remaining
tangible despite this change in state.

[0073] In the preceding description, various aspects of claimed subject
matter have been described. For purposes of explanation, systems or
configurations were set forth to provide an understanding of claimed
subject matter. However, claimed subject matter may be practiced without
those specific details. In other instances, well-known features were
omitted or simplified so as not to obscure claimed subject matter. While
certain features have been illustrated or described herein, many
modifications, substitutions, changes or equivalents will now occur to
those skilled in the art. It is, therefore, to be understood that the
appended claims are intended to cover all such modifications or changes
as fall within the true spirit of claimed subject matter.